Evidence map›Paper›PMID 36560395›Full record

ArticleVaccines2022

Improving Public Health Policy by Comparing the Public Response during the Start of COVID-19 and Monkeypox on Twitter in Germany: A Mixed Methods Study.

Tareq Al-Ahdal, David Coker, Hamzeh Awad, Abdullah Reda, Przemysław Żuratyński, Sahamoddin Khailaie

Abstract read
In one paragraph

Article in Vaccines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. The Growing Impact of Natural Language Processing in Healthcare and Public Health.Inquiry : a journal of medical care organization, provision and financing
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Tareq Al-AhdalResearch Associate, Institute of Global Health (HIGH), Heidelberg University, 69117 Heidelberg, Germany.ORCID 0000-0001-6693-4525
David CokerAdvanced Education Programs, Adjunct Faculty, Fort Hays State University, Hays, KS 67601, USA.ORCID 0000-0002-9138-2125
Hamzeh AwadA/Professor Health Information Management and Health Informatics Research Chair, Higher College of Technology, Abu Dhabi 25026, United Arab Emirates.ORCID 0000-0001-7720-3728
Abdullah RedaFaculty of Medicine, Al-Azhar University, Cairo 11651, Egypt.ORCID 0000-0002-2180-0029
Przemysław ŻuratyńskiDivision of Medical Rescue, Faculty of Health Sciences with the Institute of Maritime and Tropical Medicine, Medical University of Gdańsk, 80-210 Gdansk, Poland.ORCID 0000-0003-3498-6229
Sahamoddin KhailaieDepartment of Systems Immunology and Braunschweig Integrated Centre of Systems Biology, Helmholtz Centre for Infection Research, 38124 Braunschweig, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Little is known about monkeypox public concerns since its widespread emergence in many countries. Tweets in Germany were examined in the first three months of COVID-19 and monkeypox to examine concerns and issues raised by the public. Understanding views and positions of the public could help to shape future public health campaigns. Few qualitative studies reviewed large datasets, and the results provide the first instance of the public thinking comparing COVID-19 and monkeypox. We retrieved 15,936 tweets from Germany using query words related to both epidemics in the first three months of each one. A sequential explanatory mixed methods research joined a machine learning approach with thematic analysis using a novel rapid tweet analysis protocol. In COVID-19 tweets, there was the selfing construct or feeling part of the emerging narrative of the spread and response. In contrast, during monkeypox, the public considered othering after the fatigue of the COVID-19 response, or an impersonal feeling toward the disease. During monkeypox, coherence and reconceptualization of new and competing information produced a customer rather than a consumer/producer model. Public healthcare policy should reconsider a one-size-fits-all model during information campaigns and produce a strategic approach embedded within a customer model to educate the public about preventative measures and updates. A multidisciplinary approach could prevent and minimize mis/disinformation.

Indexed as

COVID-19monkeypoxNatural Language Processingpublic health policythematic analysisunsupervised machine learning

Identifiers

PMID36560395
PMCPMC9787903

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.